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README.md

DaSiWa Custom Nodes Collection

A high-performance collection of custom nodes for ComfyUI, optimized for video workflows, resolution management, and logic control.

Included Nodes

💎 RTX Upscaler & Refiner

State-of-the-art image and video enhancement using NVIDIA RTX Video SDK. It executes up to three sequential passes (Denoise, Deblur, and Upscale) in a single node, processing frame-by-frame to keep VRAM usage predictable and low.

  • Refine: Independent Denoise and Deblur passes.
  • Upscale: AI-powered VSR and High Bitrate upscaling.
  • Smart Sizing: Multiple resize modes including Constant Megapixel targets.
  • Efficiency: Frame-by-frame processing for minimal VRAM usage.

RTX_UpscalerRefiner.png

Full documentation →

📐 Resolution Scale Calculator

The DaSiWa Scale Calculator provides mathematically precise resolution management for high-performance video models. It uses a Constant-Area Square-Root method to ensure that your GPU VRAM usage remains stable regardless of the aspect ratio.

  • Unified Resolution Presets: Pick standard p targets from 144p to 2160p/4K or optimized megapixel tiers from one dropdown.
  • Clear Aspect Modes: IMAGE ASPECT uses the connected image shape; USE ASPECT BELOW uses the always-visible aspect controls.
  • Video-Safe Snapping: Standard, Div32, Div64, and custom divisor modes keep dimensions aligned for different model families.

ResolutionScaleCalculator.png

Full documentation →

⚡ Torch Resize

A drop-in replacement for ComfyUI's built-in resize nodes that keeps images sharp and video workflows fast without extra dependencies.

  • Sharper results: Lanczos resampling with optional sRGB-to-linear gamma correction produces cleaner upscaling and downscaling than native bilinear/bicubic.
  • Video-friendly batching: Automatically splits long frame sequences into memory-safe chunks so you never run out of VRAM, while keeping output order intact.
  • Zero extra installs: Runs entirely on the PyTorch build ComfyUI already uses — no Pillow, torchlanc, Triton, or vendor SDK required.
  • Precise sizing control: Divisible-by alignment, five aspect modes (fit, fill/crop, pad, stretch, long-side crop), and configurable crop/pad placement eliminate guesswork for downstream model constraints.
  • Alpha preserved: Transparency channels are resized independently without gamma conversion artifacts.

DaSiWa-Torch-Resize.png

Full documentation →

🎛️ Node Status Switch

The DaSiWa Node Status Switch lets you mute or bypass any node in your workflow using a single toggle. Targets are registered by wiring their outputs into the switch's input slots, which grow dynamically as you connect more nodes (up to 99).

NodeStatusSwitch.png

Full documentation →

Quick start:

  1. Add a DaSiWa Node Status Switch to your workflow
  2. Drag any output from the node(s) you want to control into the switch's target_01 input — new slots appear as you connect more
  3. Set action to mute or bypass and configure trigger_on to taste
  4. Toggle enabled directly on the switch

🎬 LTX-2 Lora Loader

The DaSiWa LTX-2 Lora Loader is a 10-slot LoRA stacker designed for LTX-2.3 video generation. LTX-2.3 is unique because it generates both video and audio from separate transformer branches. This node gives you independent control over how LoRAs affect video vs. audio.

  • Dual-Branch Control: Adjust video (V×) and audio (A×) multipliers independently per LoRA.
  • 10 LoRA Slots: Stack up to 10 LoRAs with fine-grained strength control (STR: −2.0 to +2.0).
  • Key Count Indicator: Auto-scans each LoRA to show video/audio key counts before generation.
  • 6 Themes: Switch between Jade, Neon, Studio, Chrome, OLED, and Wood color schemes.
  • Searchable UI: Quick LoRA search with live filtering in the node itself.

DaSiWa-LTX23-LoraLoader.png

Full documentation →

💾 Metadata Image Saver (Civitai Ready)

The DaSiWa Metadata Image Saver ensures your images are fully compatible with Civitai, Hugging Face, and other galleries by embedding A1111-style metadata. It automatically detects LoRAs used in the workflow and supports dynamic filenames.

  • Civitai Compatibility: Writes the standard parameters block for auto-parsing of prompts and resources.
  • LoRA Detection: Scans your workflow and appends <lora:name:weight> triggers automatically.
  • WebP Support: Full "Drag-and-Drop" workflow reconstruction support for both PNG and WebP formats.
  • Dynamic Filenames: Use placeholders like %seed%, %date%, %model%, %width%, and %height%.
  • Privacy: Toggle workflow JSON embedding to share images without exposing your full graph.

DaSiWa-MetadataImageSaver.png

Full documentation →

🎞️ Enhanced Video Combine

The DaSiWa Enhanced Video Combine turns an IMAGE batch into a high-quality video with optional ComfyUI AUDIO muxing, an in-node VHS-style preview, and a set of enhanced automations that choose safe output settings instead of relying on a fixed encoder setup.

DaSiWa Enhanced Video Combine

  • Enhanced host-aware encoding automation: Auto runtime-tests AV1 → H.265/HEVC → VP9 → H.264 and selects the first encoder that actually works on the host, preferring NVIDIA NVENC, then other GPU encoders (Intel QSV, AMD AMF, VAAPI), then software.
  • Enhanced container and codec safety automation: Chooses compatible WebM/MKV/MP4 combinations per codec and retains a mandatory H.264/MP4 fallback if every preferred combination fails.
  • Enhanced precision and preview automation: Detects 8-bit versus 10-bit source-frame precision; H.265 keeps its requested final output while an H.264 sidecar is generated automatically for browsers without HEVC playback.
  • Enhanced output automation: The node always re-encodes when queued, supports ping-pong loops, preserves optional workflow metadata, and names audio outputs with -audio.
  • Animated-image outputs: Select Animated AVIF or Animated WebP explicitly for looping image output without audio. Animated AVIF prefers GPU AV1 encoding (av1_nvenc, then other hardware encoders) and safely falls back to software; Animated WebP uses its required CPU libwebp_anim encoder.
  • Asset-panel frame automation: Enable Save first frame and/or Save last frame to write PNGs next to the video with matching names and publish the video plus each generated PNG to ComfyUI Assets.
  • Audio controls and preview behavior: Mux connected audio, select audio codec/bitrate, optionally crop the video to audio duration, and hover the in-node preview to unmute it automatically.
  • Concise diagnostics: Always writes compact ComfyUI CLI logs for codec/container selection, the actual video encoder, and the resolved audio encoder/bitrate (for example, audio=libopus/192k), plus output path and relevant fallbacks—without a logging toggle.
  • Built-in help: Click the small ? at the right side of the node title for a concise setting reference.

Full documentation →

🎬 Watermark Overlay

A professional-grade watermark tool optimized for image and video batches. It uses a stable CPU compositor with high-quality resampling and precise rotation.

  • Dynamic Random Positioning: Toggle seeded corner cycling while keeping the selected position as the start position.
  • Splash Mode: Configure dynamic fade-in and fade-out at the start and end of clips for professional branding.
  • Optical Padding: Automatically adjusts placement by the watermark's visual center of mass for perfect alignment.
  • Stable Compositing: Output frames are initialized from the source batch before the watermark region is blended, avoiding flicker and black-frame artifacts.

DaSiWa-Watermark.png

Full documentation →

🖥️ System Monitor

A compact system telemetry bar integrated directly into the ComfyUI top toolbar. The adjacent DaSiWa settings button lets you hide the monitor or choose its display mode.

  • Multi-GPU Support: Separate metrics per GPU device (NVIDIA, AMD, Intel) labeled as GPU0, GPU1, etc.
  • Resource Metrics: CPU, RAM, SWAP/Pagefile, DISK, GPU Utilization, GPU VRAM, and GPU Temperature.
  • Visual Feedback: Color-coded borders and proportional background fills (0–100%) for instant at-a-glance assessment.
  • Lite / Full Modes: Lite is the default compact toolbar view; Full shows every available metric with detailed values and a live 60-second graph.
  • Responsive Layout: Lite automatically hides lower-priority metrics when toolbar space is limited; Full is a scrollable panel that adapts to narrow screens.
  • Cross-Platform: Works on Linux and Windows with automatic fallback detection for GPU tools.
  • Independent Placement: Renders as its own toolbar element, not dependent on third-party extensions.

Lite mode

DaSiWa_System_Monitor.png

Full mode

DaSiWa_System_Monitor-full.png

Full documentation →

🔀 Random String Picker

Bridge any string/text node through DaSiWa Random String Picker to randomize prompt variants inline.

  • Text passthrough: Accepts a connected STRING input and returns a STRING output.
  • Inline variants: Replaces every {A|B|C} segment with one randomly selected option.
  • Multiple groups: Processes any number of groups independently, such as {red|blue} car in {sun|rain}.
  • Literal passthrough: Text outside complete {...} groups is left unchanged.

RandomStringPicker.png

Full documentation →

🧠 LLM / VLM Analyze

The DaSiWa LLM / VLM nodes let you run local transformers chat or vision-language models from inside a ComfyUI workflow. They accept native STRING inputs and native IMAGE batches from nodes such as Load Image or VHS frame loaders.

  • Native ComfyUI Inputs: Analyze connected text, still images, or video/image-sequence frame batches.
  • Prompt Presets: Custom system instructions, LTX-2.3/Wan2.2 video prompt enhancement, and image/video caption presets for mixed tags, tag-only, or natural language.
  • Memory Modes: Keep models cached for speed, or use full cleanup to unload DaSiWa and ComfyUI managed models before/after analysis so later image/video models recover VRAM/RAM.
  • Frame Sampling: Limit video analysis with max frames, stride, frame strategy, resize controls, context limits, and optional KV-cache reduction.
  • Local, GGUF, Ollama, or HF Models: Load full Transformers folders, local GGUF through llama.cpp, call Ollama, or download a Hugging Face repo id into ComfyUI/models/llm.

Full documentation →

🛠️ Installation

Manual install

  1. Activate your venv inside your ComfyUI folder
  2. Clone this repo into your custom_nodes folder: 
    git clone https://github.com/darksidewalker/ComfyUI-DaSiWa-Nodes
  3. Install all dependencies: 
    pip install -r requirements.txt
  4. Requirement: NVIDIA RTX GPU with drivers 530+. (Windows users may need the NVIDIA Broadcast SDK; Linux usually works out-of-the-box with the pip package).
  5. Restart ComfyUI.

Use ComfyUI-Manager

Search for DaSiWa-Nodes and install.

Credits

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